Draft:Raj Kashikar

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1. 1. 1. Raj Kashikar

• • Raj Kashikar** is a renowned researcher and academic in the fields of Artificial Intelligence (AI) and Machine Learning (ML). He is currently affiliated with the Department of Electrical Engineering at Virginia Polytechnic Institute and State University.

1. 1. 1. 1. Early Life and Education

Raj Kashikar's journey into the world of AI and ML began with his undergraduate studies in Computer Science. He pursued his master's degree in Electrical Engineering, where he developed a keen interest in machine learning algorithms and their applications.

1. 1. 1. 1. Research and Contributions

Raj Kashikar has made significant contributions to the field of AI and ML through his research and publications. Some of his notable works include:

1. **RAID-SCM: Risk Artificial Intelligence Detection - Supply Chain Model**:

  - This research integrates advanced AI techniques to enhance risk assessment and mitigation in supply chain management. The model, RAID-SCM, demonstrates significant improvements in operational efficiency, cost reduction, and response times to emerging supply chain threats.

2. **Leveraging Machine Learning for Enhanced Decision-Making in Software-Defined Networking and Network Function Virtualization**:

  - This paper explores the integration of ML with Software-Defined Networking (SDN) and Network Function Virtualization (NFV) to improve decision-making processes in network management. The study highlights the potential of ML to optimize network performance and reliability.

3. **Machine Learning Models for Intelligent Decision-Making in Network Traffic Management**:

  - This research focuses on developing ML models to enhance decision-making in network traffic management. It addresses the challenges of real-time decision-making and anomaly detection in dynamic network environments.

4. **AI-enhanced Secure Communication Protocols for Quantum Key Distribution (QKD)**:

  - Raj's research in this area aims to improve the security of communication protocols using AI-enhanced techniques for Quantum Key Distribution.

5. **RFML (Radio Frequency Machine Learning) with AWS**:

  - Raj has collaborated with Amazon Web Services (AWS) on pioneering projects in Radio Frequency Machine Learning. His work involves developing ML models to analyze and interpret radio frequency signals, enhancing the efficiency and accuracy of wireless communications. This collaboration with AWS has led to innovative solutions that leverage cloud-based machine learning platforms to address complex RF signal processing challenges.

1. 1. 1. 1. Professional Activities

Raj Kashikar is actively involved in various professional activities, including:

- Serving as a reviewer for prestigious journals and conferences in AI and ML. - Presenting his research at international conferences and symposia. - Collaborating with industry leaders to bridge the gap between academic research and practical applications.

1. 1. 1. 1. Publications and Citations

Raj Kashikar's work is widely recognized and cited in the academic community. He has authored several peer-reviewed papers and has been invited to contribute to leading journals in his field.

Raj's contributions to AI and ML have earned him several accolades.

1. 1. 1. 1. References

- Kashikar, R. (Year). RAID-SCM: Risk Artificial Intelligence Detection - Supply Chain Model. *Journal Name*. [Link to paper] - Kashikar, R. (Year). Leveraging Machine Learning for Enhanced Decision-Making in Software-Defined Networking and Network Function Virtualization. *Journal Name*. [Link to paper] - Kashikar, R. (Year). RFML with AWS: Innovations in Radio Frequency Machine Learning. *Journal Name*. [Link to paper] - [Additional references as required]

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